A couple of months ago I blogged about a major data cleansing project we were embarking on to ensure our candidate information is current. Our apprentice Rachael has been well and truly initiated into the company with this assignment and her efforts have started to make a real difference to the quality of service that we provide to both clients and candidates.
We currently have more than 7,500 candidates registered on our recruitment database. Whether we spoke to them once several years ago or we know them really well, the one constant is that we have had contact with all of them since the database was established six years ago.
During this period a lot has happened and there will be many candidates who have changed roles significantly since we last had contact with them, some of them several times, and therefore some of our data is now out of date.
Subsequently, we have been through each candidate individually, contacting them to reintroduce ourselves and establish whether they still wanted to ‘opt-in’ and remain on our database, so that we can contact them about potential job opportunities. At this point we either gathered current job and CV information or removed them from our records.
In most cases we have made contact with people quite easily, but in others we have had to make several attempts. The challenge has been deciding at what point we give up trying and simply delete them from our system. We have gone for quality over quantity and would much rather have a smaller, accurate database of candidates - all of who are in the correct skill groups and want us to contact them. By having this detail it means that we can ensure we market to them appropriately, making contact only about positions that they actually specialise in.
What have we learned?
Since beginning the project in May, Rachael has made great progress, updating more than 5,000 records.
We have learned that contractors generally reply with CVs and availability details quite quickly, but it is a very different case when dealing with permanent workers as they generally have little interest unless they are thinking about looking for a new job.
We know how crucial it is to ensure that detailed information is input accurately in the first instance. Historically our software has done this automatically, so we have established a new system whereby Rachael goes through all new applicants to ensure the correct details and CVs are uploaded.
We have also found that people’s situations change very quickly and we need to keep on top of this on an on-going basis, so we will be looking for ways to constantly improve and better manage our data to ensure accuracy. This includes a system for not keeping people on our database indefinitely.
Also, often clients become candidates, and candidates become clients, so we have to ensure we are as up to date as possible with everybody’s situation to market to them appropriately.
Moving forward, we plan to maintain more up to date candidate addresses on our system so that we can implement location-based job alerts. We will also be keeping a closer eye on where people move and aspire to move, particularly those interested in or moving from contractor to permanent placement and vice versa.
For others attempting to embark on such a project, I would recommend resourcing appropriately as without Rachael’s 100% commitment we would be at a far earlier stage. Time is also a major consideration, so be realistic about how much you can achieve in a given time frame. One thing is certain though with regards to our data cleansing; now we have started we can’t stop. The more up to date we get the more we realise that our candidate data is constantly changing, not just now but forever!
Our industry is reliant on data and without it we cannot service our clients and candidates effectively, but it now plays a central role in the day-to-day operation of many organisations. Typically companies don’t just have one source of information, they have multiple, and therefore investing in time and resource to data cleanse is critical to business success.
In case you missed it - Data Quality; practising what we preach - part 1